SAP is in the midst of a step-by-step platform revamp for a new generation of enterprise businesses. At Mobile World Congress in February, the company rebranded its Platform-as-a-Service (PaaS) offering as "SAP Cloud Platform" with a host of new tools and services. Today, at the company's Sapphire Now conference in Orlando, SAP rolled out new applications and services around blockchain, the Internet of Things (IoT), and machine learning (ML).

The array of new offerings is available both as standalone tools and packaged together as part of SAP Leonardo. Previously used to describe the company's IoT portfolio, SAP is repositioning SAP Leonardo as bespoke "innovation services" geared toward applying these new technologies to specific business processes by developing intelligent apps—and doing so within an accelerated six-to-eight week timeframe.

"We're launching a significant reframing of Leonardo as a digital innovation system," said Mike Flannagan, Senior Vice President of Analytics at SAP. "Transforming business models isn't about any given technology; it's about a lot of things working together. So, Leonardo is bringing together our software assets around IoT, machine learning, Big Data analytics, blockchain, and the SAP Cloud Platform."

Applied Machine Learning With Leonardo

At Sapphire Now, the company announced all of the pieces that can plug into SAP Leonardo depending on the given business scenario. A new offering, called "SAP Machine Learning," integrates ML into a new wave of apps, including eight brand-new ML apps debuted at Sapphire that tackle business processes from customer relationship management (CRM) to human resources (HR). The company also announced the "SAP Machine Learning Foundation," opening its ML stack to a wider ecosystem. The new ML apps include:

SAP Brand Impact: Uses deep learning to check for brand images in videos and images in near-real time for advertisers.

SAP Cash Application: Learns by observing how humans match incoming bank statements to open receivables such as invoices.

SAP CoPilot: Is a digital assistant app that applies ML to simplify human/computer interaction by using conversational messaging, integrating with apps such as G Suite and Slack.

SAP Resume Matching: Is a recruiter-focused applicant tracking (AT) app that sorts and scores candidates for open positions.

SAP Service Ticketing: Classifies incoming helpdesk tickets so they can be routed to the right agent, who is then prompted with recommended actions.

SAP's Enterprise Accelerator

Flannagan said the SAP Leonardo "accelerator" will launch to SAP customers in four first-mover industries including consumer goods, discrete manufacturing, retail, and sports & entertainment. But SAP envisions future apps tackling ML and IoT use cases such as accounts payable, banking, invoice analysis, supply chain, travel, and beyond.Flannagan explained how these innovations combine with design thinking and rapid prototyping through SAP Leonardo. The goal, he said, is to deliver an app for a specific business process in a set timeframe and without customer risk, rather than a business making a significant investment in a new technology without a clear return or a set cost.

"As we started working with customers in all corners of the world across different industries, we noticed common problems and common methodologies being used to solve those problems. Still, every company felt like they were doing it alone and doing it wrong," said Flannagan. "[Leonardo] is about solving a problem for a customer and then replicating that process. We're delivering a technology blueprint for their specific environment and what the applications, investment, and risk will look like at scale."

SAP also announced an expansion of its partnership with Google, which now includes additional certification of SAP technology and apps on Google Cloud Platform (GCP). The partnership also aims to make SAP Cloud Platform on GCP available globally, as well as future collaboration and integrations in ML, data transparency, IoT, and workplace productivity. Google and SAP have now certified SAP NetWeaver and general availability and certification of SAP HANA on GCP, and a data connector for SAP Analytics Cloud for Google Big Query.

In addition to the ML and Google announcements, SAP also unveiled new blockchain and IoT technologies as part of its cloud platform and SAP Leonardo portfolio. SAP Digital Twin, a digital IoT inspection tool based on the company's acquisition of Fedem Technology last year, uses real-time structural analysis and simulation software to let manufacturers inspect digital representations of physical IoT assets based on sensor data. The idea is to reduce the operational complexity of inspecting industrial assets on a large scale or IoT endpoints located in remote or hard-to-reach locations.

Finally, the company launched a new SAP Cloud Platform blockchain service. The system is designed to help enterprises integrate blockchain with existing business processes, applying the distributed ledger technology in scenarios such as automating IoT device validation in a production line. SAP envisions the blockchain-as-a-service offering as a way to help businesses set up and manage blockchain nodes across a swath of different industries, and the company (a Hyperledger member) aims to integrate with other tools in the blockchain ecosystem.

All of the Sapphire announcements play into SAP's larger vision for SAP Leonardo and SAP Cloud Platform. Flannagan, who previously spent more than 16 years overseeing various analytics and data management groups at Cisco, said the biggest advantage is the accelerated approach. SAP wants to give enterprises the ability to experiment with emerging technologies such as blockchain and ML, but in an environment where the business gets a ready-to-implement solution and quickly starts seeing results.

"Innovation is cool, but if you can't figure out how to scale, it doesn't help your business. We want to take things one step at a time. In six-to-eight weeks, we solve one narrowly defined business problem and show value, and then choose another and do the same. You start seeing results a little bit at a time," said Flannagan.

"Take [Italian train operator] Trenitalia," he continued. "We worked with them on IoT and predictive maintenance to move away from scheduled maintenance and only do it when necessary. Using machine learning, they saw an 8- to 10-percent reduction in maintenance costs. Now, owners and operators of any transportation asset can replicate that."

Get Our Best Stories!

This newsletter may contain advertising, deals, or affiliate links. Subscribing to a newsletter indicates your consent to our Terms of Use and Privacy Policy. You may unsubscribe from the newsletters at any time.